Build vs Buy – AI Based Recommendation Engine

kritika Published on : 17 September 2021 4 minutes

  According to Industry Arc, the market size for recommendation engines is estimated to reach 12.03 billion dollars in 2025. What’s more interesting is the fact that this number used to be only 1.14 billion dollars in 2018. IndustryArc, in … Continue reading

Build vs Buy - Recommendation Engine

 

According to Industry Arc, the market size for recommendation engines is estimated to reach 12.03 billion dollars in 2025. What’s more interesting is the fact that this number used to be only 1.14 billion dollars in 2018. IndustryArc, in its report on Recommendation Engine Market, said that the above mentioned growth is mainly driven by two things: an increase in digitization and the organization’s perspective to enhance customer satisfaction. So, if you are reading this blog, there are high chances that you are one of the stakeholders of a website aiming to increase customer satisfaction for your organization. To add to this, you are confused about whether to buy or build a recommendation engine.

Nothing much to worry about, since we have for you the buy or build recommendation engine – an ultimate checklist. 

 

Buy or Build – AI based Recommendation Engine

 

Here are the five major components of this checklist – 

  1. Time – How much time do you have before you want to start using a recommendation engine?
  2. Budget – What is your budget for a recommendation engine?
  3. Resources – How many employees can you dedicate behind the recommendation engine?
  4. Scalability – When do you assume you might need scalability in a recommendation engine?
  5. Assurance – Are you willing to try one more time if the result fails?

 

buy or build recommendation engine

 

Now that you have seen this table, read the below instructions, and check on the level you resonate with. 

1. Time

  1. Tick high if you have more than one year before you want to implement the recommendation engine
  2. Tick Medium if you are not sure or have less than one year in your hands
  3. Tick low if you have anywhere less than 6 months

 

2. Budget

  1. If you have a lot( we are not asking how much), then tick high
  2. Tick medium if you are not sure
  3. Tick low if you are on a tight budget

 

3. Resources

  1. If you have an entire dev team of say 40 to 50 people that you can dedicate into building a high performing recommendation engine, then you must tick high.
  2. Tick Medium if you are not sure
  3. Tick low if there’s hardly any employee that you can dedicate into this

 

Alie

 

4. Scalability 

  1. If your organization is growing rapidly, and you know in a couple of months, you would want to scale the recommendation engine, then tick high.
  2. If you think there will be a reasonable gap before your organization needs scalability, then tick medium. 
  3. If you can not see any reason for scalability, then tick low.

 

5. Assurance

  1. If you need assurity that the final outcome should be perfect, then tick high
  2. If you think you can manage with revisions of the final outcome, then tick medium
  3. If you really don’t care about the outcome in the short term, but obviously, you want the end result to be perfect, then tick low

 

Now, have you completed the checklist? If yes, then look at the below table that will help you in understanding what you need to do based on your choices. 

 

Recommendation engine build or buy

 

You can use permutations and combinations if you wish to with these outcomes, but our recommendation would be, if you have got even one ‘buy’ in your suggestion column, then at least explore all the recommendation engine available; best would be if you take the free trial so that you can understand what you and your organization needs. 

 

Conclusion

The recommendation engine, if used right, has the power to make your business a global leader. Don’t believe us? If so, then we have two words for you – Netflix and Amazon. Netflix currently has a revenue of 25 billion USD, but it was struggling to survive two decades back. Moreover, according to the reports by McKinsey & Company, Amazon has a revenue of 280 billion dollars, and 35 percent of this revenue comes from their recommendation engine. So, what is stopping you from becoming the best version of you(Your organization, basically)? We suggest, follow the above chart, come to a conclusion, and if you end up deciding that your organization needs to buy a recommendation engine, then explore all the options available. Start with knowing our product, Alie – an AI-based recommendation engine. You can find multiple algorithms and real-time recommendations. More importantly, it can be integrated with any platform in only a few steps; read the blog How to integrate recommendation engines to know more in detail. Try Alie’s 14-day free trial to understand more about how the recommendation engine works. 

 

Written by: kritika

Kritika Verma is an Associate Content Writer and works with Muvi Marketing Team. She is an inbound marketing professional and ensures high-quality traffic on the Muvi website through her blogs, articles, and more. She has an engineering background but always had a knack for writing. In her free time, she is either on Quora or on chess.com (Mostly losing).

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